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Titlebook: Causal Nets, Interventionism, and Mechanisms; Philosophical Founda Alexander Gebharter Book 2017 Springer International Publishing AG 2017

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發(fā)表于 2025-3-21 16:27:34 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Causal Nets, Interventionism, and Mechanisms
副標題Philosophical Founda
編輯Alexander Gebharter
視頻videohttp://file.papertrans.cn/223/222623/222623.mp4
概述Supports the theory of causal Bayes nets by an inference to the best explanation.Offers a novel discussion of the relationship between Woodward’s interventionist theory of causation and the theory of
叢書名稱Synthese Library
圖書封面Titlebook: Causal Nets, Interventionism, and Mechanisms; Philosophical Founda Alexander Gebharter Book 2017 Springer International Publishing AG 2017
描述.This monograph looks at causal nets from a philosophical point of view. The author shows that one can build a general philosophical theory of causation on the basis of the causal nets framework that can be fruitfully used to shed new light on philosophical issues. Coverage includes both a theoretical as well as application-oriented approach to the subject..The author first counters David Hume’s challenge about whether causation is something ontologically real. The idea behind this is that good metaphysical concepts should behave analogously to good theoretical concepts in scientific theories. In the process, the author offers support for the theory of causal nets as indeed being a correct theory of causation..Next, the book offers an application-oriented approach to the subject. The author shows that causal nets can investigate philosophical issues related to causation. He does this by means of two exemplary applications. The first consists of an evaluation of Jim Woodward’s interventionist theory of causation. The second offers a contribution to the new mechanist debate..Introductory chapters outline all the formal basics required. This helps make the book useful for those who ar
出版日期Book 2017
關鍵詞Causal Bayes Nets; Causal Modeling; Causation; Empirical Content; Explanatory Warrant; Inference to the b
版次1
doihttps://doi.org/10.1007/978-3-319-49908-6
isbn_softcover978-3-319-84270-7
isbn_ebook978-3-319-49908-6Series ISSN 0166-6991 Series E-ISSN 2542-8292
issn_series 0166-6991
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 20:29:05 | 只看該作者
Causal Nets,In this chapter I give a brief overview of the central notions and definitions of the causal nets framework, which was developed in detail by Pearl and Spirtes, Glymour, and Scheines. I also begin to develop and justify an axiomatization of the causal nets framework, to be continued and finished in Chap.?.
板凳
發(fā)表于 2025-3-22 02:03:07 | 只看該作者
https://doi.org/10.1007/978-3-662-68090-2theoretical part on the philosophical foundations of the theory of causal Bayes nets and a more application oriented part. The former part (Chap. .) supports the theory of causal Bayes nets by an inference to the best explanation. It can also be seen as a response to David Hume’s skeptical challenge
地板
發(fā)表于 2025-3-22 08:01:52 | 只看該作者
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發(fā)表于 2025-3-22 12:06:01 | 只看該作者
Der Weg zur Ordnung im sozialen Miteinanderm provides the best explanation for two statistical phenomena. In the second part I present several results about the empirical content of different versions (i.e., combination of axioms) of the theory of causal nets. Both parts together show that causation satisfies the same modern standards as the
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發(fā)表于 2025-3-22 15:41:59 | 只看該作者
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發(fā)表于 2025-3-22 17:46:59 | 只看該作者
Korpusstudie 1: Formen von OKAY, Russo, and Williamson and present three problems with their approach. I then present my alternative approach of how to represent mechanisms, compare it with Casini et?al.’s approach, and discuss Casini’s recent objections to my approach. I also make a suggestion how constitutive relevance relation
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發(fā)表于 2025-3-23 08:57:30 | 只看該作者
Formal Preliminaries,relation’, ‘function’, and ‘structure’ are explicated. The probabilistic concepts relevant for later chapters are illustrated. I also explain the most important graph-theoretical concepts and introduce Bayesian networks. Most of the presented concepts are illustrated by means of simple examples.
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